About the job
About the Role
Hopper is on the lookout for an outstanding Principal Product Manager with a strong foundation in AI to spearhead the development and management of our intelligence and reconciliation systems across Flights, Hotels, Cars, and Ancillaries.
In this pivotal role, you will oversee systems that establish pricing intelligence, supplier performance metrics, and financial accuracy across millions of travel transactions.
Your mission will be to design and enhance model-driven infrastructures that consistently analyze transactional data, generate reference pricing, identify performance fluctuations, reconcile financial transactions, and uphold revenue integrity in real-time.
This foundational role exists at the crossroads of marketplace economics, machine learning, and financial systems. You will collaborate closely with Data Science and Engineering teams to implement predictive models, develop evaluation frameworks, manage model lifecycles, and ensure that our intelligence systems are measurable, adaptable, and reliable.
Your contributions will significantly influence partner economics, enhance supplier transparency, and strengthen HTS’s global commerce platform.
Day-to-Day Responsibilities:
Lead the comprehensive strategy and roadmap for pricing intelligence, supplier performance insights, and financial reconciliation across all travel sectors.
Architect and refine reference pricing systems using predictive modeling, elasticity signals, competitive benchmarking, and real-time anomaly detection.Create the supplier intelligence framework, converting transactional data into automated performance indicators, demand insights, and pricing diagnostics.
Establish and maintain the authoritative source of truth for revenue, margin, take rate, transactions, and cancellations across various systems and partners.
Develop model evaluation, monitoring, and feedback systems, including drift detection and continuous enhancement strategies.Deploy automated reconciliation and anomaly detection frameworks to proactively highlight financial discrepancies at scale.
Facilitate cross-functional collaboration with Engineering, Data Science, Finance, Commercial, and Supply to deliver robust, model-integrated infrastructure.